Environment Protection Engineering
Vol. 40 2014 No. 1
DOI: 10.5277/epe140112
ANNA WĘGRZYN1, SEBASTIAN ŻABCZYŃSKI1
MONITORING OF BACTERIAL BIODIVERSITY
IN ANAEROBIC MEMBRANE BIOREACTORS (AnMBRs)
DEALING WITH WASTEWATER CONTAINING X-RAY
CONTRAST MEDIA COMPOUNDS
Iodinated contrast media compounds (ICM) have been identified in wastewater within the last 20 years. In this study, the biodiversity of activated sludge in anaerobic membrane bioreactors deal-ing with synthetic hospital wastewater with addition of ICM was investigated, usdeal-ing fluorescent in
situ hybridization (FISH) and denaturing gradient gel electrophoresis (DGGE). During the adaptation
of microorganisms to anaerobic growth conditions and to ICM presence, differences in the content of
Alpha- and Betaproteobacteria were noted and bioreactors showed higher biological diversity
(H = 2.9), suggesting that ICM were not toxic to the bacteria. The long sludge age had the strongest influence on the composition of activated sludge biocenosis.
1. INTRODUCTION
Many pharmaceuticals such as iodinated contrast media compounds (ICM), lipid regulators, antiphlogistics, β-blockers, antiepileptics, antibiotics, and illicit drugs have been detected in the aquatic environment within the last 20 years [1]. Studies have shown that unmetabolised drugs (and the products of their metabolic transformations) enter the municipal sewage system and then are directed to the wastewater treatment plant. Treatment processes in the plant fail to completely eliminate drugs from wastewater. In consequence, drugs, together with treated wastewater, are released into surface waters [2].
Although the concentration of pharmaceutical compounds encountered in most aquatic environments currently are at very low levels (from ng/dm3 to μg/dm3), their
_________________________
1Environmental Biotechnology Department, Faculty of Power and Environmental Engineering, The
Silesian University of Technology, ul. Akademicka 2, 44-100 Gliwice, Poland, corresponding author A. Węgrzyn, e-mail: anna.wegrzyn@polsl.pl
continuous input may constitute a long-term potential risk for aquatic and terrestrial organisms, including human beings [3].
Iodinated X-ray contrast media are the most widely used pharmaceutical com-pounds for imaging soft tissues, internal organs, and blood vessels and can be admin-istered to humans at doses up to 300 g per diagnostic session [4]. The annual world-wide consumption of ICM is approximately 3.5×106 kg [5]. They are of low human
toxicity and are hardly metabolized. ICM are excreted mostly unchanged within 24 h (>95%) [6]. Most of ICM are derivatives of 2,4,6-triiodobenzoic acid with polar car-boxyl and hydroxyl moieties in their chains. Some are ionic – have one or several free carboxyl groups, others are amide derivatives and, as such, are neutral compounds.
Based on our research, we can state that specific contrast agents can be found in wastewater in Poland in the concentrations of up to 30 μg/dm3 [7]. A higher
concen-tration (1 mg/dm3) was determined for hospital wastewater [8] and Gartiser et al. [9]
reported that X-ray contrast media and their metabolites contain organic bound halo-gens and therefore contribute to adsorbable organic halides (AOX).
The elimination of ICM from wastewater using biological processes of activated sludge proved to be a major challenge regardless of the used technology [10]. In con-ventional activated sludge processes (CASP), ICM removal efficiency was estimated to 40%. The highest removal efficiency (60%) was observed for membrane bioreac-tors [10]. These reacbioreac-tors have become very commonly used due to their advantages over settler-operated systems. The membranes are able to retain particles of different sizes, depending on the membrane type within the reactor [11]. Application of mem-branes in activated sludge systems enables a much more effective separation of solids from wastewater. It should be noted that elimination of contrast media in anaerobic conditions is more economically attractive than the aerobic processes, mainly due to the cost of aeration and disposal of excess sludge.
Transformation of ICM has been investigated in sludge systems, as well as in sed-iment-water systems; however the results have been inconsistent [4, 6, 12, 13]. In ad-dition to the lack of consensus concerning the biotransformation of iodinated X-ray contrast media and characterization of microbial transformation pathways, there is also a scarcity of information about changes of a bacterial community structure in activated sludge induced by synthetic hospital wastewater containing ICM.
The aim of the study was to estimate biodiversity of activated sludge in anaerobic membrane bioreactors dealing with synthetic hospital wastewater containing iodinated X-ray contrast media (diatrizoate, iodipamide and iohexol). In the first stage of the experiment, the adaptation of microorganisms to anaerobic growth conditions and to ICM presence was observed. In the second stage, the adaptation to different sludge ages (40, 70 and 100 days) was investigated. Temporal changes in the bacterial com-munities were investigated by culture-independent methods – fluorescent in situ hy-bridization (FISH) and denaturing gradient gel electrophoresis (DGGE).
Bacterial biodiversity in anaerobic membrane bioreactors 153
2. MATERIALS AND METHODS
Reactor details and operational data. Bacteriological material from three
com-pletely mixed, laboratory-scale anaerobic membrane bioreactors was used in this study. The membrane (flat-sheet Kubota, pore size of 0.4 μm) was submerged in the bioreactor (Fig. 1). Diffusion of oxygen was limited by a polystyrene layer. Activated sludge from a municipal wastewater treatment plant (Gliwice) was used as a seed.
Fig. 1. Scheme of the membrane bioreactor
The study was conducted in two stages: in the first, the adaptation of microorgan-isms to anaerobic growth conditions and to ICM presence was observed (0–6 months) and in the second, when sludge age was established (7–8 months).
Sludge age was calculated as follows:
r e V X SRT Q X = (1)
where: Vr is the reactor volume, dm3, X – concentration of biomass within the reactor,
g SS/dm3, Q
e – amount of excess sludge, dm3/d.
influent effluent filtration module membrane bioreactor agitator
Since in the MBR reactor X – numerator is the same as the denominator, then r e V SRT Q = (1a)
In order to obtain a particular sludge age, a constant and appropriate volume of acti-vated sludge (Qe = Vr/SRT) was removed daily from each reactor. Technical parameters
of bioreactors used in the study, in the stage of age regulation, are shown in Table 1.
T a b l e 1 Technical parameters of the bioreactors used in the study in the stage of age sludge regulation
Technical parameter Bioreactor A Bioreactor B Bioreactor C
Bioreactor volume, dm3 45 45 45
SRT, d 40 70 100
Oxygen concentration, mg O2/dm3 0–1 0–1 0–0.76
HRT, h 67.2 67.2 67.2
Flow speed, dm3/d 9.2–20.1 11.2–19.4 12.2–18.7
Volatile suspended solids, g SS/dm3 1.88–5.15 3.06–5.41 4.05–5.62
Amount of excess sludge, dm3/d 1.125 0.64 0.45
Organic loading rate, mg COD/(dm3·d) 0.19–0.55 0.22–0.52 0.24–0.51
Organic sludge loading rate, mg COD/(g SS·d) 0.04–0.25 0.04–0.15 0.04–0.11 Efficiency of COD removal, % 37–80 43–94 68–95
Temperature, °C 19.5–26.1 19.6–26 19.7–25.9
pH 8–9 8–9 8–9
The reactors were fed with a synthetic hospital wastewater containing the follow-ing: CH3COONa (1.670 g/dm3) used as a source of carbon and energy, KH2PO4
(0.044 g/dm3), and NH4Cl (0.250 g/dm3) used as a source of nitrogen and phosphorus,
respectively; diatrizoate (0.001 g/dm3); iohexol (0.001 g/dm3) and iodipamid
(0.0015 g/dm3). Properties of ICM used in the studies are shown in Table 2. The
concentration of biomass in the bioreactors was determined by dry weight method (PN-72/C-04559/02). Concentration of ICM in the samples was determined by reversce phase high performance liquid chromatography (RP HPLC), UltiMate 3000, Dionex.
Fluorescent in situ hybridization. Samples were fixed with a paraformaldehyde
solu-tion (4% paraformaldehyde in phosphate buffered saline, PBS, pH 7.2) at 4 °C for 3 h and subsequently washed in PBS. Fixed samples were stored in PBS and ethanol (1:1 v/v) solution at –20 °C. In situ hybridization was performed as described previously by Daims [14]. 16S rRNA targeted fluorescently labeled oligonucleotide probes and the sequences are listed in Table 3. The probes EUB338, EUB338 II and EUB338 III were mixed to-gether (EUB338 mix) in the proportion 1:1:1 in order to detect all bacteria. Details on the chosen oligonucleotide probes are available at probeBase [15]. The probes were 5′-labeled
with prob F IUPA Mole Skel CAS Mole weig Osm mOs App EUB EUB EUB ALF BET Com GA Com h FLUOS (5(6)-bes and unlabele
Formula D AC name 3,5-diac 2,4,6-tri ecular C letal S number ecular ght, Da molality, sm/kg H2O 1
plication angiogracompute
r Probe B 338 Mo B 338 II Pla B 338 III Ver F968 Alp exc T42a Bet mp-BET42a a AM42a Ga mp-GAM42a b a – used as unlabe b – used as unlabe Bacterial biodiver -carboxy-fluores ed competitor oli Propert Diatrizoate cetamido- iiodobenzoic acid 3-ph -2 11H9I3N2O4 117-96-4 613.92 500 –2000 aphy, urography, ed tomography ch ch rRNA-targeted olig Target organisms ost bacteria anctomycetales rrucomicrobiales phaproteobacteria, cept of Rickettsiales taproteobacteria ammaproteobacteria
eled competitor tog eled competitor tog
rsity in anaerobic m
scein- N-hydrox igonucleotides w
ties of ICM used in Iodipami -{5-[(3-carboxy-2,4 henyl)carbamoyl]pe 2,4,6-triiodobenzoic C20H14I6N 606-17-1139.29 664 holangiography, holecystography gonucleotide probe Se 5′- GCT GCC T 5′- GCA GCC A 5′- GCT GCC A 5′- GGT AAG 5′- GCC TTC C 5′- GCC TTC C a 5′- GCC TTC C 5′- GCC TTC C gether with probe B gether with probe G
membrane bioreact
xysuccinimide e were obtained fro
n the studies id ,6-triiodo- entanamido} acid 1-N, prop prop benz N2O6 7 9 mye arthr
es used in the study equence (5′–3′) TCC CGT AGG AG ACC CGT AGG TG ACC CGT AGG TG GTT CTG CGC GT CCA CTT CGT TT CCA CAT CGT TT CCA CAT CGT TT CCA CTT CGT TT BET42a. GAM42a. tors ester) or Cy3. B om Bionovo, Po T Iohexol ,3-N-bis(2,3-dihydro pyl)-5-[N-(2,3 –dihy pyl)acetamido]-2,4,6 zene-1,3-dicarboxam C19H26I3N3O9 66108-95-0 821.14 322–844 lography, rography T y [19] Formam GT -3′ 0–5 GT -3′ GT -3′ TT -3′ 20 -3′ 35 T -3′ a T -3′ 35 -3′ b 155 Both the oland. T a b l e 2 oxy- ydroxy 6-triiodo mide T a b l e 3 mide [%] 50% 0% 5% a 5% b
Prior to microscope observations, samples were embedded in Citifluor (Citifluor, Ltd, UK) to reduce fluorochrome fading. A fluorescence microscope (MOTIC BA400T) was used to examine the microbial community. Image processing was per-formed using Motic Images Plus 2.0 software package. For cell quantification, ImageJ software was used.
Activated sludge samples for DGGE, DNA extraction and PCR conditions.
Acti-vated sludge samples (volume of 50 cm3) were collected from bioreactors (A, B, C)
at 2 month intervals and stored at –20 °C. Total genomic DNA was extracted from 0.2 g of the activated sludge samples using FastDNA® spin kit for soil (MP
Biomedicals, USA) according to manufacturer’s instructions and stored at –20 °C until PCR amplification. Primers [16]: 968F with a GC clamp (5′ CGC CCG GGG CGC GCC CCG GGC GGG GCG GGG GCA CGG GGG GAA CGC GAAGAA CCT TAC 3′) and 1401R (5′ CGG TGT GTA CAA GGC CC 3′) were used for par-tial 16S rRNA bacterial gene PCR amplification. PCR was carried out in a 30 μl (total volume) reaction mixture containing 18.9 μl of sterile MiliQ water, 6 μl of PCR buffer (GoFlexi TAQ, Promega), 2.4 μl of MgCl2 (2 mM), 0.3 μl of both
pri-mers (5 pmol/μl), 1.3 μl dNTPs (20 pmol/μl), 0.5 μl of genomic DNA and 0.3 μl Taq DNA polymerase (1.5 U).
PCR amplification was performed using an Eppendorf thermal cycler and the following steps: (1) the initial denaturation (5 min at 94 °C); (2) 30 cycles, each single cycle consisting of denaturation (1 min at 94 °C), annealing (1 min at 53 °C), and elongation (1 min at 72 °C); and (3) the final extension step (10 min at 72 °C). Products were evaluated in agarose gel (0.8% w/vol agarose, 1× TBE buffer), stained with ethidium bromide (1% w/vol.) in MiliQ water and photographed under UV light.
DGGE denaturing gradient gel electrophoresis. The DGGE of PCR products
ob-tained in reaction with 8F and 536R primers were performed using the Dcode Univer-sal Mutation Detection System (BioRad). The polyacrylamide gel (8% v/v with a gra-dient of 30–60% denaturant) was run for 9 h at 55 V in a 1 × TAE buffer at a constant temperature of 60 °C. The gel was stained with SYBR Gold (1:10 000, Invitrogen) in MiliQ water for 20 min and washed with MiliQ water twice for 15 min, then visual-ized under UV light and photographed.
Numerical analysis of the DGGE fingerprints. The DGGE banding patterns with
16S rDNA PCR products were analyzed using the Quantity One 1D Software (BioRad). The structural diversity of the bacterial community was estimated based on the Shannon–Weaver diversity index, H [17] estimated from the relative band intensi-ties obtained from the DGGE fingerprints.
Bacterial biodiversity in anaerobic membrane bioreactors 157
3. RESULTS AND DISCUSSION
3.1. CHANGES OF PROTEOBACTERIA CLASSES ANALYZED BY FISH
Initial analyses were carried out basing on the activated sludge originating from the wastewater treatment plant. At the beginning of the experiment, the percentage of various Proteobacteria classes was characteristic of that of the activated sludge from a municipal wastewater treatment plant. The community structure profile indicated the
Betaproteobacteria to be the numerically dominant group of bacteria, i.e. 47% of
bac-terial cells were Betaproteobacteria (BET42a⁄EUBmix), followed by Alphaproteobac-
teria at 31% (ALF968⁄EUBmix) and Gammaproteobacteria at 19% (GAM42a
⁄EUBmix) (Fig. 2). In probing COD removing activated sludges from various munici-pal plants with oligonucleotide probes specific for Proteobacteria, Wagner et al. [18] demonstrated the dominance of Proteobacteria, which together comprised 60–75% microbial cells. Wagner and Amann [19] reported members of the Betaproteobacteria as playing a major role in the microbial consortia of activated sludge plants and alpha- and gammaproteobacterial classes being less abundant.
Fig. 2. Percentages of group-specific probes relative to EUBmix counts in sample from WWTP
Degenaar et al. [20] showed similar community structure profile during domestic wastewater treatment process. The numerically dominant group was Betaproteo-
bacteria (33%), followed by Alphaproteobacteria at 26% and Gammaproteobacteria
at 15%. Mudaly et al. [21] showed a similar trend of bacterial predominance, with the
Betaproteobacteria comprising 22% of total cells, followed by Alphaproteobacteria
(19%) and Gammaproteobacteria (17%) in a laboratory scale EBPR sludge-treating domestic wastewater. These results reflect a similar scenario in full scale processes treating domestic wastewater. Wagner et al. [18] identified members of the
Betaproteobacteria predominating in aerated activated sludge systems with 42% of
0 20 40 60 80 100
Raw activated sludge
EU Bm ix (% ) ALF968 BET42a
cells binding to BET42a with respect to probe EUB. Wong et al. [22] surveyed wastewater treatment plants in Japan and suggest the Betaproteobacteria to be the most abundant group in two treatment plants treating domestic wastewater and ac-counted for 20% and 30% of EUBmix-stained cells, respectively.
In the fourth month of the experiment, during the adaptation of microorganisms to anaerobic growth conditions and to high ICM concentrations, differences in the con-tent of Alpha- and Betaproteobacteria were noted (Fig. 3).
Fig. 3. Percentages of group-specific probes relative to EUBmix, counts in samples from bioreactor A, B and C in the fourth month of the experiment
The community structure profile indicated the Alphaproteobacteria to be the nu-merically dominant group of Bacteria, i.e. 48–51% of bacterial cells were Alpha-
proteobacteria (ALF968⁄EUBmix), followed by Betaproteobacteria at 24–34%
(BET42a⁄EUBmix) and Gammaproteobacteria at 17–21% (GAM42a⁄ EUBmix). In the fourth month of the experiment, the content of Alphaproteobacteria was higher by 19% and that of Betaproteobacteria was lower by 19% as related to the initial analyses. The content of Gammaproteobacteria has not changed significantly in relation to the beginning of the experiment. The Alphaproteobacteria include most of the oligotrophic Proteobacteria (those capable of growing at low nutrient levels). However, the Betaproteobacteria overlap the Gammaproteobacteria metabolically but tend to use substances that diffuse from organic decomposition in the anaerobic zone of habitats. Some of these bacteria use hydrogen, ammonia, methane, volatile fatty acids, and other substances [23].
After adaptation of microorganisms to anaerobic growth conditions and to ICM presence, in the eight month of the experiment, the content of Betaproteobacteria increased in bioreactors (Fig. 4).
The community structure profile indicated the Betaproteobacteria to be the nu-merically dominant group of bacteria, i.e. 44–49% of bacterial cells were Betaproteo-
bacteria (BET42a⁄EUBmix), followed by Alphaproteobacteria at 36–37% (ALF968-
⁄EUBmix) and Gammaproteobacteria at 14–17% (GAM42a⁄ EUBmix).
0 20 40 60 80 100
Bioreactor A Bioreactor B Bioreactor C
EU Bm ix (% ) ALF968 BET42a
Bacterial biodiversity in anaerobic membrane bioreactors 159
Fig. 4. Percentages of group-specific probes relative to EUBmix, counts in samples from bioreactor A, B and C and biomass concentration in eighth month of the experiment
In the eighth month of the experiment, the content of Betaproteobacteria was higher by 17% and that of Alphaproteobacteria was lower by 14% as related to the previous analyses in the fourth month. The content of Gammaproteobacteria has not changed significantly (decrease by 3%).
3.2. THE EFFICIENCY OF ICM REMOVAL
In eighth month of the study, differences in the biomass concentrations were noted (Fig. 4). The biomass concentration in the bioreactor A was about 2.2 g/dm3 and in the
bioreactors B and C – 3.5 g/dm3 and 4.1 g/dm3, respectively. With comparable
techno-logical parameters and ICM removal efficiency, it can be assumed, that the lower bi-omass content should be related with higher microbial activity in the elimination of contaminants. The efficiency of ICM removal in the bioreactors is shown in Table 4.
T a b l e 4 The efficiency of ICM removal in the eighth month of the experiment
Bioreactor [SRT, days] Efficiency of ICM removal [%] Iohexol Iodipamid Diatrizoate
A (40) 17 49 85
B (70) 19 53 86
C (100) 12 57 90
Biotransformation of ICM has been investigated in sludge systems, as well as in sediment–water systems and in all studies the mineralization of ICM was incomplete. However, mineralization was observed for a precursor of ICM, 5-amino-2,4,6-triiodophthalic acid, in a two-stage anaerobic-aerobic reactor [24]. The formation of most ICM biotransformation products in the aerobic conditions can be explained by
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 0 20 40 60 80 100
Bioreactor A Bioreactor B Bioreactor C
S us p en de d s o lid s [g SS/ d m 3] EU B m ix (% ) ALF968 BET42a
succession of one, two or three of the following biochemical reaction types: oxidation of the primary or secondary alcohol groups, decarboxylation and cleavage of N–C bond [25]. If an anaerobic digester is present in a sewage treatment plant or in anaero-bic parts of sediments, the deiodination process of ICM was observed [24, 26].
Kalsch [13] and Haiss and Kümmerer [4] suggest that partial degradation of diatrizoate in aerobic and anaerobic conditions is possible. In this study, the ionic diatrizoate removal efficiency was high in all three bioreactors (85–90%). However, HPLC analysis indicated that triiodinated aromatic ring was not modified completely. Despite the high removal efficiency of diatrizoate, its metabolite was detected. It can be assumed that the change in diatrizoate structure was due to removal of one or two atoms of iodine (not published data). The non-ionic iodipamid removal efficiency was lower but acceptable (49–57%) and highest removal efficiency was noted for longest sludge age. The non-ionic iohexol removal efficiency was low (12–19%). There is few data on the removal of iodipamid and iohexol from wastewater. Busetti et al. [27] showed microfiltration and reverse osmosis were effective treatment for removal of iodpipamid and iohexol. Jeong et al. [3] demonstrated higher removal efficiency of iohexol by ozonation (35–55%) and it appears that loss of iodine from the ICM should result in more biodegradable products during treatment.
3.3. DGGE ANALYSIS OF THE BACTERIAL COMMUNITY
The fingerprints obtained from DGGE separation of 16S rRNA gene fragments are shown in Fig. 5. The DNA-based DGGE pattern had changed in all three bioreac-tors during the experiment.
Fig. 5. DGGE pattern of fragments of 16S rRNA genes of the size of ca. 500 bp amplified using DNA obtained from activated sludge samples;
A, B, C – bioreactors; 0, 3, 4, 6, 8 – month of the experiment
Bacterial biodiversity in anaerobic membrane bioreactors 161
The dendrogram (Fig. 6) obtained from DGGE fingerprint analysis presents the value of similarity among activated sludge samples. This could be calculated by summarizing the length of branches connecting particular samples of the dendrogram. The lower this value, the higher similarity the samples present. After two months of the experiment, sam-ples collected from bioreactors revealed high similarity values, which suggests similar changes in microbial communities. The reason for such situation could be activated sludge volume reduction, adaptation of microorganisms to anaerobic growth conditions and to ICM presence. For the next six months, the sample from bioreactor C seems to be less congruent to the bioreactors A and B. There is a possibility that long sludge age had strongly influenced the activated sludge biocenosis composition.
Fig. 6. DGGE tree based on neighbor-joining clustering method; A, B, C – bioreactors, 0, 3, 4, 6, 8 – month of the experiment
Biodiversity, that is biological diversity in an ecosystem, is expressed in statistical terms by means of the Shannon biodiversity index [17]. Temporal dynamics of the Shannon–Weaver diversity values (H) for activated sludge samples are shown in Fig. 7.
Fig. 7. Temporal dynamics of the Shannon–Weaver diversity values (H) for activated sludge samples from bioreactor A, B and C
0 2A 2B 2C 4A 4B 4C 6A 6B 6C 8A 8B 8C 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 0 2 4 6 8 D iv er sit y in d ex , H time (months)
In the second month of the experiment, the biological diversity increased in all three bioreactors to HA = 3.19, HB = 2.96 and HC = 3.01, respectively. The reason for
such situation could be the composition of synthetic wastewater, containing easy available source of carbon and energy. Furthermore, studies have shown that in short-term tests with bacteria (Vibrio fischeri, Pseudomonas putida) no toxic effects were detected at concentrations of ICM as high as 10 g/dm3 [6]. In the bioreactor A, in the
fourth month of the experiment, the diversity decreased to 2.78 and in sixth and eighth month slightly increased (3.0). In the bioreactor B, the decrease in biodiversity was observed (2.65) in the sixth month of the experiment, but in the eighth month an in-crease was noted (3.19). The variability of the bacterial community according to the results obtained in the Shannon–Weaver index estimations was the highest in the bio-reactor C. The diversity increased in the sixth month of the experiment (3.29) but in the eighth month a noticeable decrease was observed (1.97). The reason for such situa-tion could be long sludge age in bioreactor C and development of a specialized bacte-rial community capable of transforming ICM. To verify these assumptions it would be necessary to carry out more detailed molecular investigations.
4. CONCLUSIONS
Fluorescence in situ hybridization (FISH) and denaturing gradient gel electropho-resis (DGGE) allowed us to estimate differences in biodiversity of activated sludge, in anaerobic membrane bioreactors dealing with synthetic hospital wastewater with addi-tion of ICM. Initial analysis indicated that the percentage of the Alpha-, Beta- and
Gammaproteobacteria classes was characteristic of that of an activated sludge from
a municipal wastewater treatment plant. In the fourth month of the experiment, during the adaptation of microorganisms to anaerobic growth conditions and to ICM pres-ence, the content of Alphaproteobacteria increased in bioreactors. However, in the eighth month of the experiment, after SRT adaptation, the Betaproteobacteria was the numerically dominant class of Proteobacteria. The reason for such situation could be the ability of Betaproteobacteria to use substances that diffuse from organic decom-position in the anaerobic conditions. In quantitative analysis of Proteobacteria in acti-vated sludge, the biomass concentration should be taken into consideration. The major differences in biodiversity was noted in a bioreactor with activated sludge of the age of 100 days. The reason for that situation could be formation of a specialized microbi-al community but more detailed molecular investigations are required.
ACKNOWLEDGEMENTS
The authors express their gratitude to Aneta Bacik and Sandra Markefka for their laboratory help. The research was supported by the Polish Ministry of Science and Higher Education, Grant No. N N523 746340.
Bacterial biodiversity in anaerobic membrane bioreactors 163
REFERENCES
[1] SCHULZ M.,LÖFFLER D.,WAGNER M.,TERNES T.A., Transformation of the X-ray contrast medium
iopromide in soil and biological wastewater treatment, Environ. Sci. Technol., 2008, 42 (19), 7207.
[2] KÜMMERER K., Pharmaceuticals in the Environment: Sources, Fate, Effects and Risks, [in:]
Pharmaceuticals in the Environment, K. Kümmerer (Ed.), Springer, Berlin 2004, 521.
[3] JEONG J.,JUNG J., COOPER W.J., SONG W., Degradation mechanisms and kinetic studies for the
treatment of X-ray contrast media compounds by advanced oxidation/reduction processes, Water
Res., 2010, 44 (15), 4391.
[4] HAISS A., KÜMMERER K., Biodegradability of the X-ray contrast compound diatrizoic acid, identifi-cation of aerobic degradation products and effects against sewage sludge microorganisms,
Chemo-sphere, 2006, 62 (2), 294.
[5] PÉREZ S., BARCELÓ D., Fate and occurrence of X-ray contrast media in the environment, Anal. Bioanal. Chem., 2007, 387 (4), 1235.
[6] STEGER-HARTMANN T.,LÄNGE R.,SCHWEINFURTH H., Environmental risk assessment for the widely used
iodinated X-Ray contrast agent Iopromide (Ultravist), Ecotoxicol. Environ. Saf., 1999, 42 (3), 274.
[7] ŻABCZYNSKI S.,SURMACZ-GÓRSKA J.,MIKSCH K.,FELIS E.,TERNES T.,Fate of PPCPs in sequencing batch reactor (SBR), ACEE, 2009, 2 (3), 127.
[8] VERLICCHI P.,GALLETTI A.,PETROVIC M.,BARCELÓ D., Hospital effluents as a source of emerging
pollutants: An overview of micropollutants and sustainable treatment options, J. Hydrol., 2010, 389
(3–4), 416.
[9] GARTISER S., BRINKER L., ERBE T., KÜMMERER K., WILLMUND R., Contamination of Hospital Wastewater with Hazardous Compounds as Defined by § 7a WHG, Acta Hydrochim. Hydrobiol.,
1996, 24 (2), 90.
[10] EU KNAPPE final report, http://environmentalhealthcollaborative.org/images/KNAPPE_REPORT _FINAL.pdf03.12.12.
[11] CHARCOSSET C., Membrane process in biotechnology: an overview, Biotechnol. Adv., 2006, 24 (5), 482. [12] LECOUTURIER D., ROCHEX A., LEBEAULT J.-M., The mineralization of 5-amino-2,4,6-triiodoiso-
phthalic acid by a two-stage fixed-bed reactor, Water Res., 2008, 42 (10–11), 2491.
[13] KALSCH W., Biodegradation of the iodinated X-ray contrast media diatrizoate and iopromide, Sci.
Total Environ., 1999, 225 (1–2), 143.
[14] DAIMS H.,STOECKER K.,WAGNER M., Fluorescence in situ hybridization for the detection of prokar-yotes, [in:] Advanced Methods in Molecular Microbial Ecology, A.M. Osborn, C.J. Smith (Eds.),
Bios-Garland, Abingdon, UK, 2005, 213.
[15] LOY A.,HORN M.,WAGNER M., ProbeBase an online resource for rRNA-targeted oligonucleotide
probes, Nucleic Acids Res., 2003, 31 (1), 514.
[16] CYDZIK-KWIATKOWSKA A.,CIESIELSKI S.,WOJNOWSKA-BARYŁA I., Bacterial amoA and 16S rRNA
genes expression in activated sludge during aeration phase in sequencing batch reactor, Pol. J. Nat.
Sci., 2007, 22 (2), 246.
[17] SHANNON C.E.,WEAVER W., The Mathematical Theory of Communication, University Illinois Press,
Urbana, USA, 1963.
[18] WAGNER M.,AMANN R.,LEMMER H.,SCHLEIFER K.H., Probing activated sludge with oligonucleo-tides specific for Proteobacteria: inadequacy of culture-dependent methods for describing microbial community structure, Appl. Environ. Microbiol., 1993, 59 (5), 1520.
[19] WAGNER M.,AMANN R.I., Molecular techniques for determining microbial community structures in
activated sludge, [in:] Microbial community analysis: The key to the design of biological wastewater treatment systems, T.E. Cloete, N.Y.O. Muyima (Eds.), I.A.W.Q. Scientific and Technical Report
[20] DEGENAAR A.P.,ISMAIL A.,BUX F., Comparative evaluation of the microbial community in biologi-cal processes treating industrial and domestic wastewaters, J. Appl. Microbiol., 2008, 104 (2), 353.
[21] MUDALY D.D.,ATKINSON B.W.,BUX F., Microbial community profile of a biological excess phos-phorus removal (BEPR) activated sludge system using a cultivation independent approach, Water
S.A., 2000, 26 (3), 343.
[22] WONG M.T.,MINO T.,SEVIOUR R.J.,ONUKI M.,LIU W.T., In situ identification and characterization
of the microbial community structure of full-scale enhanced biological phosphorus removal plants in Japan, Water Res., 2005, 39 (13), 2901.
[23] PRESCOTT L.M., Microbiology, 5th Ed., The McGraw-Hill, New York 2002.
[24] LECOUTURIER D., GODON J.J., LEBEAULT, J.M., Phylogenetic analysis of an anaerobic microbial
consortium deiodinating 5-amino-2,4,6-triiodooisophthalic acid, Appl. Microbiol. Biotechnol., 2003, 62
(4), 400.
[25] KORMOS J.L.,SCHULZ M.,KOHLER H.-P.E.,TERNES T.A., Biotransformation of selected iodinated X-ray contrast media and characterization of microbial transformation pathways, Environ. Sci.
Technol., 2010, 44 (13), 4998.
[26] LECOUTURIER D.,ROCHEX A.,LEBEAULT J.M.,Enrichment and properties of an anaerobic mixed culture that reductively deiodinates 5-amino-2,4,6-triiodooisophthalic acid, an X-ray contrast agent precursor, Appl. Microbiol. Biotechnol., 2003, 62 (5–6), 550.
[27] BUSETTI F.,LINGE K.L.,BLYTHE J.W.,HEITZ A., Rapid analysis of iodinated X-ray contrast media in secondary and tertiary treated wastewater by direct injection liquid chromatography-tandem mass spectrometry, J. Chromatogr. A, 2008 (1213), 208.
